Managing data privacy and information safety

ABSTRACT

Automatically screen data associated with a user that may have already been shared on a social network or about to be shared on the social network for a potential security risk and assign a risk score to the data. If the assigned risk score is above a threshold risk score, a risk mitigation measure is generated and executed.

BACKGROUND

The present invention relates generally to the field of protection ofdata processing, and more particularly to managing data privacy andinformation safety on social networks.

Social network users uploading information onto a social network mayinadvertently share sensitive information online. For example, a userposting vacation pictures to a social network in real-time while stillon vacation may expose the security of the user's belongings back at theuser's residence to undesirable acts by ill-minded intruders who may usesuch sensitive information to plan a burglary in the user's residenceduring user's absence.

SUMMARY

According to an embodiment of the invention, a method for dynamicallyevaluating and mitigating risk associated with data shared on a socialnetwork is provided. The method may receive data associated with a user,by a computing device, for posting on a social network. The method mayassign a category to the received data. The method may assign a riskscore to the received data based on predefined risk scores associatedwith the assigned category. The method may also generate a riskmitigation measure based on the assigned risk score being greater than athreshold risk score, the risk mitigation measure comprising one or moreof: (i) modifying the data, (ii) deleting the data, (iii) retaining thedata wherein the data is not posted to the social network untilreceiving an instruction to post the data to the social network, (iv)removing metadata associated with the received data, and (v)communicating a message regarding the data to a device.

According to another embodiment of the invention, a computer programproduct for dynamically evaluating and mitigating risk associated withdata shared on a social network is provided. The computer programproduct includes one or more computer-readable storage media and programinstructions stored on the one or more computer-readable storage media,the program instructions executable by a processor. The computer programproduct may include program instructions to receive data associated witha user, by a computing device, for posting on a social network. Thecomputer program product may also include program instructions to assigna category to the received data. The computer program product may alsoinclude program instructions to assign a risk score to the received databased on predefined risk scores associated with the assigned category.The computer program product may also include program instructions togenerate a risk mitigation measure based on the assigned risk scorebeing greater than a threshold risk score, the risk mitigation measurecomprising one or more of: (i) modifying the data, (ii) deleting thedata, (iii) retaining the data wherein the data is not posted to thesocial network until receiving an instruction to post the data to thesocial network, (iv) removing metadata associated with the receiveddata, and (v) communicating a message regarding the data to a device.

According to another embodiment of the invention, a computer system fordynamically evaluating and mitigating risk associated with data sharedon a social network is provided. The computer system includes one ormore computer processors, one or more computer-readable storage media,and program instructions stored on the computer-readable storage mediafor execution by at least one of the one or more processors. Thecomputer system includes program instructions to receive data associatedwith a user, by a computing device, for posting on a social network. Thecomputer system may also include program instructions to assign acategory to the received data. The computer system may also includeprogram instructions to assign a risk score to the received data basedon predefined risk scores associated with the assigned category. Thecomputer system may also include program instructions to generate a riskmitigation measure based on the assigned risk score being greater than athreshold risk score, the risk mitigation measure comprising one or moreof: (i) modifying the data, (ii) deleting the data, (iii) retaining thedata wherein the data is not posted to the social network untilreceiving an instruction to post the data to the social network, (iv)removing metadata associated with the received data, and (v)communicating a message regarding the data to a device.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a functional block diagram illustrating a data privacy andinformation safety environment, in accordance with an embodiment of thepresent invention.

FIG. 2 is a functional block diagram illustrating modules of a dataprivacy and information safety environment program, in accordance withone embodiment of the present invention.

FIG. 3 is a flowchart illustrating operational steps of the data privacyand information safety program, in accordance with an embodiment of thepresent invention.

FIG. 4 is a functional block diagram illustrating a cloud computing nodeaccording to an embodiment of the present invention.

FIG. 5 is a functional block diagram illustrating a cloud computingenvironment according to an embodiment of the present invention.

FIG. 6 is a functional block diagram illustrating abstraction modellayers according to an embodiment of the present invention.

The drawings are not necessarily to scale. The drawings are merelyschematic representations, not intended to portray specific parametersof the invention. The drawings are intended to depict only typicalembodiments of the invention. In the drawings, like numbering representslike elements.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. This invention may, however, be embodied inmany different forms and should not be construed as limited to theexemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope of this invention to thoseskilled in the art. In the description, details of well-known featuresand techniques may be omitted to avoid unnecessarily obscuring thepresented embodiments.

References in the specification to “one embodiment”, “an embodiment”,“an example embodiment”, etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with oneembodiment, it is submitted that it is within the knowledge of oneskilled in the art to affect such feature, structure, or characteristicin connection with other embodiments whether or not explicitlydescribed.

A social network user posting information to a social network mayinadvertently share sensitive information online which an ill-mindedintruder may use to plan illegal activities negatively affecting theuser, for example, by scheduling a burglary in the user's residencewhile the user is on a vacation based on information on an impendingvacation included in one of the user's posts to the social network.However, it may be cumbersome for a typical user to manually analyze andpredict all prospective undesirable side-effects that may result fromthe user's posts to the social network. It may be desirable to have asystem that may automatically screen posts to a social network impactinga user for potential security risks before or soon after they get postedonline.

Embodiments of the present invention may automatically screen dataassociated with a user that may have already been shared on a socialnetwork or about to be shared on the social network for a potentialsecurity risk. The data being screened may include a social network post(“SNP”) made on a social network web-page or “wall”. The screening mayoccur prior to a SNP being posted or immediately after it is posted on asocial network. Embodiments of the present invention may assign a riskinformation category and a risk score based on predefined risk scoresassociated with the assigned category to the data. If the assigned riskscore is above a threshold risk score, embodiments of the presentinvention may generate and execute a risk mitigation measure.

As used herein, “social network” refers to a computer network connectingentities, such as people or organizations, by a set of socialrelationships, such as friendship, co-working, or a communityrepresenting a group of members sharing common interests orcharacteristics. A social network may include blogs and forums. Thesocial network may foster relationships between its members, therebyoffering a higher level of affiliation and trust than other online mediathrough which users can interact with each other such as electronicmessage boards or forums. The social network may display social networkposts (SNP) posted by a plurality of users on the social network. Socialnetwork may also refer to a computer application or data connecting suchentities by such social relationships. Social network may provide anavenue for users to post information and respond to previously postedinformation by self and others. Members of a social network may elect toexchange information with or transmit information to all participantswithin the social network, a minority of participants, or a group thatencompasses other participants plus others that may be connected by asecond or subsequent degree links (such as e.g., friends of friends).Exchange with or among second or subsequent degree members may also bedenied, limited or restricted for safety and security reasons. A socialnetworks may include an administrator that uses lists to control themembership in the social network.

Embodiments of the present invention may utilize data analytic systemswell known in the art to categorize a SNP and to assign a risk score tothe SNP if it the SNP deemed to present a potential security risk andapply a risk mitigation measure associated with the SNP. Embodiments ofthe present invention may compute a risk score for a risk that the usermay have no control of or no knowledge of. The risk score may becomputed using data analytic systems known in the art based on dynamicinputs and trending data, in addition to static factors. Embodiments ofthe present invention may present the user with options to eitherautomatically or manually mitigate a risk. Embodiments of the presentinvention may also provide the user with the ability to override a riskmitigation measure implemented by embodiments of the present invention.

Risk mitigation measures may include: alerting the user of the potentialsecurity risk, editing the SNP, removing a portion of the SNP, deletingthe entire SNP, hiding a portion of the SNP or the whole SNP fromcertain viewers on a social network, blurring a portion of a digitalimage that may form part of the SNP. Embodiments of the presentinvention may customize its service features based on factors that mayinclude: a user's risk tolerance level, locale of the user, valuablesowned by the user, frequency of real-time SNPs uploaded by the user,frequency of real-time SNPs uploaded members in user's network, generalcontent of SNPs uploaded by the user and by members in the user'snetwork, and characteristics associated with the user. Embodiments ofthe present invention may use updated security threat and security riskinformation available from public and private domains, and analyze themfor predicting a security risk contained in data present in a specificSNP in light of a user's individual characteristics including aspectssuch as: activity type, location, time, age, marital status, profession,household income, gender, ethnicity, recent criminal activity in anarea, and type of data shared on the social network. For example, whenrobberies occur in the user's neighborhood in residences of individualswith a similar personal profile as the user, embodiments of the presentinvention may generate an alert customized to the user.

Embodiments of the present invention may computationally evaluatewhether a whole SNP or a portion of a SNP should be shared on a socialnetwork, thereby providing for granular control of managing securityrisks posed by a SNP. Embodiments of the present invention may provideadvantages over manual risk management of SNPs by a human administrator.An administrator manually reviewing SNPs for such a manual riskmitigation mechanism may have limitations such as: time delay inimplementing the risk mitigation mechanism; in-consistent subjectivecriteria being exercised; administrator knowledge of risks beingoutdated; inefficiency arising from fast changing risk scenarios;administrator not capable of making a decision or making an incorrectdecision in a given context due to complexity of information; and,special training requirements needed to keep administrator up to date onemerging risks, among others.

Embodiments of the present invention may automatically apply a riskmitigation measure in a scenario where a user may not have posted a SNPbut may be exposed to a security risk due to a SNP by the user'sroommate indicating that both the user and the roommate are currently ata vacation spot located far from a location where their rooms may besituated. Embodiments of the present invention may also automaticallyapply risk mitigation measures in an embodiment where the user's SNP maynot pose a security risk, but one or more follow-up SNPs being posted byothers in response to the user's SNP may generate a potential securityrisk. For example, a follow-up SNP by a member in user's network maypoint out that an expensive car remains parked at a garage in user'sresidence while user is out of town, thus generating a risk. Embodimentsof the present invention may recommend and apply risk mitigationmeasures in such a scenario.

In one scenario, embodiments of the present invention may just remove auser's current location included in the user's SNP as a risk mitigationmeasure. In another scenario, embodiments of the present invention maydelay the posting of a SNP to a social network temporally until asecurity risk is eliminated. In another scenario, embodiments of thepresent invention may allow sensitive data in a SNP to be selectivelyviewable only by a few people within the user's network that are on alist of “trusted members”. In another scenario, embodiments of thepresent invention may allow a complete unedited version of a SNP to beavailable for view by a few trusted members in user's network whilesimultaneously allowing an edited version that has been stripped ofsensitive information, to be viewable by others. In another scenario,embodiments of the present invention may strip off metadata such as, forexample, GPS location information and time stamps associated with a SNPbefore it gets posted to a social network. In another scenario,embodiments of the present invention may blur a portion of a digitalimage in order that a landmark present in the image may be renderedunrecognizable before SNP is posted to a social network. In anotherscenario, embodiments of the present invention may trim a portion of adigital image. In another scenario, embodiments of the present inventionmay permit only selected people in a user's social network to viewcertain data flagged to be sensitive.

The present invention will now be described in detail with reference tothe figures. All brand names and/or trademarks used herein are theproperty of their respective owners.

FIG. 1 is a functional block diagram illustrating an exemplary dataprivacy and information safety environment 100 for managing data privacyand information safety associated with data posted to social networks.In various embodiments of the present invention data privacy andinformation safety environment 100 may include a computing device 102and a server 112, connected over network 110.

The network 110 represents a worldwide collection of networks andgateways, such as the Internet, that use various protocols tocommunicate with one another, such as Lightweight Directory AccessProtocol (LDAP), Transport Control Protocol/Internet Protocol (TCP/IP),Hypertext Transport Protocol (HTTP), Wireless Application Protocol(WAP), etc. Network 110 may also include a number of different types ofnetworks, such as, for example, an intranet, a local area network (LAN),or a wide area network (WAN).

Computing device 102 represents a network connected user computingdevice on which data privacy and information safety associated with dataposted to social networks will be managed, in accordance with variousembodiments of the invention. The computing device 102 may be, forexample, a mobile device, a smart phone, a personal digital assistant, anetbook, a laptop computer, a tablet computer, a desktop computer, orany type of computing device capable of running a program and accessinga network, in accordance with one or more embodiments of the invention.In an embodiment, the computing device 102, and the server 112, whichwill be explained later, may form part of an enterprise system.Computing device 102 may include internal and external hardwarecomponents, as depicted and described in further detail below withreference to FIG. 4. In other embodiments, computing device 102 mayrepresent, for example, a local computing device 54A-N in a cloudcomputing environment, as described in relation to FIGS. 4, 5, and 6,below. In an embodiment, system components within computing device 102,for example, RAM 30 (FIG. 4), may include read-only registers and/orother data stores that contain device, network ID, user, systemdate/time, and other system and user information that may be accessible,for example, by application programming interfaces (APIs). Computingdevice 102 may also support data and screen capture, for example, by oneor more proprietary or open source screen capture APIs.

In one embodiment, the computing device 102 may include applicationssuch as a social network application 108 and a data privacy &information safety 104. Social network application 108 represents aninterface that may be used to access various social networks. In anexemplary embodiment, Social network application 108 may be, forexample, an application that interfaces with a network application, suchas social network server interface 122 on server 112, both described inmore detail below, or interfaces with a local application residing oncomputing device 102, such as data privacy & information safety 104,described in more detail below. In other embodiments, social networkapplication 108 may represent an interface that is integral to a localapplication residing on computing device 102, such as the data privacy &information safety 104. In various embodiments, Social networkapplication 108 may support monitoring of data included in SNPs sharedon social networks impacting a user, for example, by one or moreproprietary or open source APIs or add-ons, so that an API or add-on maysignal that data impacting the user has been shared on a social network.

Social network server interface 122 represents an interface that dataprivacy & information safety 104, social network application 108 and auser utilizes to interact with a social network. In one embodiment,social network server interface 122 represents an application thatupdates or otherwise augments the information available on the riskmitigation data store 116, to be described later. In one embodiment,extension application 126 may represent an application that may permit auser to select the right risk tolerance level and the appropriateprivacy setting. In one embodiment, social network server interface 122may interact with data privacy & information safety 104 in updating thecontents of the risk mitigation data store 116. In this mode, extensionapplication 126 may permit a user to receive up-to-date information onnew and evolving security risks based on the user's characteristics.

Risk mitigation data store 116 represents a database that includesinformation associated with risk mitigation. In one embodiment, riskmitigation data store 116 may interact with databases available on theworldwide web through social network server interface 122 to collect andindex security threats and risks associated with data included in SNPs.In one embodiment, risk mitigation data store 116, through socialnetwork server interface 122, may represent a gateway to riskcataloguing knowledge databases such as, for example, an online publicsafety information database maintained by a governmental entity or aprivate entity. In one embodiment, risk mitigation data store 116 mayrepresent a database that includes organized collection of datacontaining information corresponding to risk information categories. Inone embodiment, risk mitigation data store 116 may represent a databasethat contains a listing of all databases available on the worldwide webthat contain information related to security risks associated with dataincluded in SNPs shared on social networks. In one embodiment, riskmitigation data store 116 may be updated with new information via manualuser entry through a user interface on computing device 102 or throughother means such as by automatic periodic data transfers from an onlinedatabase to risk mitigation data store 116. In an exemplary embodiment,risk mitigation data store 116 is stored locally on server 112, howeverin other embodiments, context-sensitive translation & reformatting datastore 116 may be located remotely and accessed via a network such asnetwork 110.

Data privacy & information safety 104 operates to dynamically evaluate,categorize, assign a security risk score, recommend and undertake a riskmitigation measure to mitigate a security risk associated with dataincluded in a social network post (SNP) shared on a social network.

FIG. 2 depicts modules that form part of data privacy & informationsafety 104 of FIG. 1 that, in one embodiment, may include: socialnetwork post receiving module 202, risk information category analysismodule 204, risk score assigning module 206, risk score comparisonmodule 208, risk mitigation measure determination module 210, riskmitigation measure recommendation module 212, and risk mitigationmeasure application module 214.

Social network post receiving module 202 may operate to monitor a user'sonline social network account on an ongoing basis and receive dataassociated with an original or secondary SNP shared on a social networkor to be shared on the social network. Risk information categoryanalysis module 204 may operate to analyze data in the SNP for thepresence of any potential security threats or risks to the user from thedata in the SNP. Risk score assigning module 206 may operate to assign arisk score for an identified risk information category that was assignedby risk information category analysis module 204. Risk score comparisonmodule 208 may operate to compare the sum of all assigned risk scoresunder all identified risk information categories for the data in the SNPwith the sum of the threshold risk scores found in a table comprisingthreshold risk scores associated with multiple risk informationcategories. Risk mitigation measure determination module 210 may operateto determine one or more risk mitigation measures that may reduce,minimize or neutralize the security risk associated with the data. Riskmitigation measure recommendation module 212 may operate to recommend arisk mitigation measure based on a determination made by risk mitigationmeasure determination module 210. Risk mitigation measure applicationmodule 214 may operate to apply the risk mitigation mechanism identifiedby risk mitigation measure determination module 210 and recommended byrisk mitigation measure recommendation module 212.

FIG. 3 is a flowchart depicting operational steps of data privacy &information safety 104, in accordance with one embodiment of the presentinvention. Steps depicted in FIG. 3 may be implemented using one or moremodules of a computer program such as the data privacy & informationsafety 104, and executed by a processor of a computer such as computingdevice 102 or server 112.

Social network post receiving module 202 may monitor a user's onlinesocial network account on an ongoing basis and at 301 a, social networkpost receiving module 202 may receive data associated with an originalSNP shared on a social network or to be shared on the social network. Inone embodiment, the SNP may be shared on a user's personal web-page onthe social network either by the user or a source associated with theuser. In one embodiment, the source may represent another personconnected to the user and authorized by the user to share data on theuser's personal web-page on the social network. The received data mayinclude text, digital images, audio and video.

In one embodiment, at 301 b, social network post receiving module 202may receive a secondary SNP posted to the social network that mayrepresent data associated with an original post by the user. In oneembodiment, the secondary SNP may represent data corresponding to a postthat includes information related to the user, but not posted by theuser, but posted by another source. In one embodiment, social networkpost receiving module 202 may identify an association between theoriginal SNP and the secondary SNP.

At 303, risk information category analysis module 204 may analyze theSNP for the presence of any potential security threats or risks to theuser from the data in the SNP. Risk information category analysis module204 may accomplish this by first identifying one or more riskinformation categories associated with the data.

At 305, risk information category analysis module 204 may identify oneor more risk information categories associated with the data. The riskinformation categories assigned by risk information category analysismodule 204 include: time, location, activity type, trend, frequency ofrepeated occurrence of an event, and targeted population associated withthe data. As illustrative examples, the risk information categories mayinclude: a targeted population of children between five years old andten years old, female teenagers between the ages of 16 and 18 years old,people residing in individual houses, home owners, teenagers, andseniors above 70 years old; locations that cannot be reached from theU.S. mainland such as tourist resorts in the Caribbean islands; and,house break-in events that occur more often than 50 incidents/monthwithin a city. In determining all risk information categories associatedwith the data, risk information category analysis module 204 may accessinformation stored in risk mitigation data store 116. In one embodiment,risk information category analysis module 204 may access a dataanalytics engine (not shown) via network 110 to help identify one ormore risk information categories associated with the received data. Inone embodiment, risk information category analysis module 204 may assignmore than one risk information categories to a single set of data.

In an exemplary embodiment that includes a securing risk of residencesof individuals of Chinese ethnicity being burglarized during the ChineseNew Year may assign the following risk information categories to thedata included in a SNP: location (is user expected to be away from homefor a period greater than a predefined time duration); time (does thedata describe an event scheduled to occur in the future or at present);activity (does the data describe an activity that is expected to occurlonger than a predefined time duration); and, ethnicity (whether theuser is of Chinese ancestry).

In one exemplary embodiment, in order to identify a risk informationcategory of location, risk information category analysis module 204 maydetermine whether a location of the user may be identified from thedata. In one scenario, the location may be inferred by a geographicallocation spelt out in the data. In another scenario, it may be inferredby a famous physical landmark included in a digital image present in thedata. The same data may also include a time category associated with it,such as for example, a text string included in the data indicating thata picture included in the data was taken 10 days ago.

At 307, risk score assigning module 206 may assign a risk score for anidentified risk information category that was assigned by riskinformation category analysis module 204. Risk score assigning module206 may assign the risk score for the risk information category based ona sensitive item contained in the data. The sensitive item may include:a timeliness of a statement contained in the data, a location indicatedin the data, a precision of the statement contained in the data, anactivity indicated in the data, and a risk-susceptible item contained inthe data. In assigning the risk score, risk score assigning module 206may access information available from the risk mitigation data store 116and information available on the worldwide web and accessible via socialnetwork server interface 122. Risk score assigning module 206 mayutilize such accessed information in order to assign a risk score databased on predefined risk scores associated with the assigned category,as catalogued in a table format available within or through the riskmitigation data store 116. In one embodiment, assignment of the riskscore may be based on one or more characteristics associated with theuser, the characteristics including: an activity type mentioned in thedata in the SNP, a location indicated in the data, a time mentioned inthe data, an age of the user, a marital status of the user, a professionof the user, an household income associated with the user, a gender ofthe user, an ethnicity associated with the user, and a recent criminalactivity in an area associated with the user. In one embodiment, riskscore assigning module 206 may use a defined social network privacy goalof the user to determine the risk score associated with a riskinformation category corresponding to the data included in the SNP.

In an exemplary embodiment that includes a risk information category oftime, risk score assigning module 206 may assign a risk score based onpredefined characteristics associated with the user as follows: an eventdescribed in the data occurred in the past=risk score of 0; event tooccur at least one month in the future=risk score of 1; and eventoccurring at the instant the data was posted=risk score of 2; and eventto occur within the next 30 days=risk score of 3.

In an exemplary embodiment that includes a risk information category offrequency of repeated occurrence of an event that corresponds to severalchildren kidnapping incidents that recently occurred in the city ofMiami, Fla. risk score assigning module 206 may assign a risk scorebased on predefined characteristics associated with the user as follows:a user with children vacationing in Albany, N.Y.=risk score of 0; a userwith children vacationing in Miami, Fla.=risk score of 0; and a userwith children permanently residing in Miami, Fla.=risk score of 2.

Risk score assigning module 206 may then calculate a sum of all assignedrisk scores under all identified risk information categories for thedata. In one embodiment, risk score assigning module 206 may calculate aweighted average of all assigned risk scores under all identified riskinformation categories for the data. Generally, different risk scoresassigned to different identified risk information categories may carry adifferent weight on a security risk on the user from the SNP dependingon the characteristics associated with the user. In one embodiment, riskscore assigning module 206 may use other statistical analysis methodsknown in the art to incorporate all assigned risk scores associated withthe data depending on the relative security risks posed by each of theassigned risk scores.

At 309, risk score comparison module 208 may compare the sum of allassigned risk scores under all identified risk information categoriesfor the data in the SNP with the sum of the threshold risk scores foundin a table comprising threshold risk scores associated with multiplerisk information categories, the threshold risk scores in the tablebeing customized for one or more characteristics associated with theuser.

In one embodiment, the table may reside in the risk mitigation datastore and accessible by risk score assigning module 206 via the network110. In instances where the sum is greater than the threshold risk scorein the table, it would indicate that there is a security risk to theuser from the data is deemed unsafe and therefore a risk mitigationmeasure may be needed. When the sum is greater than the threshold riskscore, risk score assigning module 206 may transfer the data and theassociated analyses to risk mitigation measure determination module 210.

At 311, risk mitigation measure determination module 210 may operate todetermine one or more risk mitigation measures that may reduce, minimizeor neutralize the security risk associated with the data. The riskmitigation measures evaluated by risk mitigation measure determinationmodule 210 may include: modifying the data, deleting the data, retainingthe data wherein the data is not posted to the social network componentuntil receiving an instruction to post the data to the social network,removing metadata associated with the received data, and communicating amessage regarding the data to a device. In one embodiment recommending arisk mitigation measure may be based on a risk tolerance setting of theuser.

At 313, risk mitigation measure recommendation module 212 may operate torecommend a risk mitigation measure based on a determination made byrisk mitigation measure determination module 210. In one scenario, therisk mitigation measure recommendation may include a suggestion to justremove a user's current location included in the user's SNP as a riskmitigation measure. In another scenario, the risk mitigation measurerecommendation may include a suggestion to delay the posting of a SNP toa social network temporally until a security risk is eliminated. Inanother scenario, the risk mitigation measure recommendation may includea suggestion to allow sensitive data in a SNP to be selectively viewableonly by a few people within the user's network that are on a list of“trusted members”. In another scenario, the risk mitigation measurerecommendation may include a suggestion to allow a complete uneditedversion of a SNP to be available for view by a few trusted members inuser's network while simultaneously allowing an edited version that hasbeen stripped of sensitive information, to be viewable by others. Inanother scenario, the risk mitigation measure recommendation may includea suggestion to strip off metadata such as, for example, GPS locationinformation and time stamps associated with a SNP before it gets postedto a social network. In another scenario, the risk mitigation measurerecommendation may include a suggestion to blur a portion of a digitalimage in order that a landmark present in the image may be renderedunrecognizable before SNP is posted to a social network. In anotherscenario, the risk mitigation measure recommendation may include asuggestion to trim a portion of a digital image. In another scenario therisk mitigation measure recommendation may include a suggestion forpermitting only selected individuals in a user's social network to viewcertain data flagged to be sensitive. In another scenario, the riskmitigation measure recommendation may include posting the data on asocial network after a defined period of time has elapsed. In anotherscenario, may include a suggestion for permitting only selectedindividuals in the user's social network to be able to view the wholeunedited SNP after a defined period of time has elapsed. In anotherscenario, the risk mitigation measure recommendation may include acombination of two or more mitigation measure suggestions mentionedabove.

Risk mitigation measure recommendation module 212 may communicate therisk mitigation measure recommendation to the user using understandablelanguage. In one embodiment, risk mitigation measure recommendationmodule 212 may display a message on a GUI display of the computingdevice indicating the risk score and the risk mitigation measure that isbeing recommended for that risk score.

At 315, risk mitigation measure application module 214 may operate toapply the risk mitigation mechanism identified in step 313. In oneembodiment applying, a risk mitigation measure may be based on a risktolerance setting of the user. In one embodiment where the data in a SNPis previously shared on the social network, applying a risk mitigationmeasure may include generating new data based on applying a riskmitigation measure and replacing the data on the social network with thenew data. In one embodiment, risk mitigation measure recommendationmodule 212 may automatically apply a risk mitigation measure withoutfirst recommending the same to the user. In one embodiment, Executingthe risk mitigation measure may include SNP modification including:removing one or more text strings contained in the data, blurring aportion of a digital image included in the data, deleting a portion of adigital image included in the data, and permitting a selected group ofindividuals to view the data. Executing the risk mitigation measure mayalso include deleting or erasing the entire SNP. Executing the riskmitigation measure may also include retaining the SNP and delayingposting of the SNP to the social network, and storing the same in adatabase. Executing the risk mitigation measure may also includeremoving metadata associated with the SNP including removing a locationmetadata, and a time stamp metadata. Finally, executing the riskmitigation measure may also include communicating a message includesending an alert to a mobile device. In one embodiment, risk mitigationmeasure recommendation module 212 may upload a modified SNP the socialnetwork after a risk mitigation measure has been applied to it.

The programs described herein are identified based upon the applicationfor which they are implemented in a specific embodiment of theinvention. However, it should be appreciated that any particular programnomenclature herein is used merely for convenience, and thus theinvention should not be limited to use solely in any specificapplication identified and/or implied by such nomenclature.

Based on the foregoing, a computer system, method, and computer programproduct have been disclosed. However, numerous modifications andsubstitutions can be made without deviating from the scope of thepresent invention. Therefore, the present invention has been disclosedby way of example and not limitation.

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,embodiments of the present invention are capable of being implemented inconjunction with any other type of computing environment now known orlater developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring now to FIG. 4, a schematic of an example of a cloud computingnode is shown. Cloud computing node 10 is only one example of a suitablecloud computing node and is not intended to suggest any limitation as tothe scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthhereinabove.

In cloud computing node 10 there is a computer system/server 12, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 12 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 4, computer system/server 12 in cloud computing node 10is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 12 may include, but are not limitedto, one or more processors or processing units 16, a system memory 28,and a bus 18 that couples various system components including systemmemory 28 to processor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing device, a display 24, etc.;one or more devices that enable a user to interact with computersystem/server 12; and/or any devices (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing devices. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 5, illustrative cloud computing environment 50 isdepicted. As shown, cloud computing environment 50 comprises one or morecloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Nodes 10 maycommunicate with one another. They may be grouped (not shown) physicallyor virtually, in one or more networks, such as Private, Community,Public, or Hybrid clouds as described hereinabove, or a combinationthereof. This allows cloud computing environment 50 to offerinfrastructure, platforms and/or software as services for which a cloudconsumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 2 are intended to be illustrative only and that computing nodes10 and cloud computing environment 50 can communicate with any type ofcomputerized device over any type of network and/or network addressableconnection (e.g., using a web browser).

Referring now to FIG. 6, a set of functional abstraction layers providedby cloud computing environment 50 (FIG. 5) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and, data privacy & information safetyprogram 96.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The many features and advantages of the present invention are apparentfrom the written description, and thus, it is intended by the appendedclaims to cover all such features and advantages of the invention.Further, since numerous modifications and changes will readily occur tothose skilled in the art, it is not desired to limit the invention tothe exact construction and operation as illustrated and described.Hence, all suitable modifications and equivalents may be considered tofall within the scope of the invention.

What is claimed is:
 1. A computer implemented method for dynamicallyevaluating and mitigating risk associated with data shared on a socialnetwork, the method comprising: receiving, by a computing device, dataassociated with a user for posting on a social network, wherein thereceived data comprises at least one of text, digital images, audio orvideo; assigning, by the computing device, a category to the receiveddata; assigning, by the computing device, a risk score to the receiveddata based on predefined risk scores associated with the assignedcategory; generating, by the computing device, a risk mitigation measurebased on the assigned risk score being greater than a threshold riskscore, wherein the threshold risk score is determined based on inputfrom the user, wherein generating the risk mitigation measure is basedon a defined social network data sharing setting associated with theuser, wherein the risk mitigation measure comprises at least one of: (i)modifying the data, wherein modifying the data comprises removing one ormore text strings contained in the data, blurring a portion of a digitalimage included in the data, deleting a portion of a digital imageincluded in the data, and permitting a selected group of individuals toview the data, (ii) deleting the data, wherein deleting the datacomprises erasing the received data; (iii) retaining the data whereinthe data is not posted to the social network until receiving aninstruction to post the data to the social network, wherein retainingthe data comprises delaying a posting of the data to the social network,and storing the data in a database, (iv) removing metadata associatedwith the received data, wherein removing metadata associated with thereceived data comprises removing at least one of a location metadata ora time stamp metadata, (v) communicating a message regarding the data toa device, wherein communicating a message comprises sending an alert toa mobile device; executing, by the computing device, the risk mitigationmeasure; and posting, by the computing device, the modified data to thesocial network.